JanusVLN employs dual implicit neural memory to separate spatial geometry and semantic info, boosting vision-language navigation.

Shuang Zeng, Dekang Qi, Xinyuan Chang et al.

Proposes a multi-level MOWI framework analyzing hallucinations, revealing data biases and model mechanisms affecting output fidelity.

Zhengyi Ho, Siyuan Liang, Dacheng Tao

Introduces Visual Test-Time Scaling (VTTS) with iterative perception, boosting multimodal reasoning by over 5% on benchmarks.

Ziang Yan, Xinhao Li, Yinan He et al.

Seedream 4.0 uses an efficient diffusion transformer and VAE to enhance high-res multimodal image generation.

Team Seedream, :, Yunpeng Chen et al.

UniPixel unifies pixel-level perception and reasoning, achieving top performance on 10 benchmarks with 3B/7B models.

Ye Liu, Zongyang Ma, Junfu Pu et al.

Do Modern Video-LLMs Need to Listen? By integrating audio encoders, LLaVA-OneVision enhances cross-modal reasoning.

Geewook Kim, Minjoon Seo

SD-VLM enhances VLM's spatial understanding with MSMU dataset and depth positional encoding, outperforming GPT-4o and Intern-VL3-78B.

Pingyi Chen, Yujing Lou, Shen Cao et al.

SPFSplatV2 enables efficient pose-free 3D Gaussian splatting from sparse views, achieving state-of-the-art performance.

Ranran Huang, Krystian Mikolajczyk

Proposed a self-supervised depth estimation method using mixture distribution to enhance boundary sharpness, achieving a 35% improvement.

Aurélien Cecille, Stefan Duffner, Franck Davoine et al.

ScaleCUA leverages cross-platform data to train large-scale GUI agents, achieving 94.4% accuracy on benchmarks.

Zhaoyang Liu, Jingjing Xie, Zichen Ding et al.

GenExam is a multidisciplinary text-to-image benchmark with 1000 samples across 10 subjects, integrating detailed prompts, ground-truth images, and fine-grained scoring.

Zhaokai Wang, Penghao Yin, Xiangyu Zhao et al.

UM-Depth enhances monocular depth estimation with motion and uncertainty, excelling on KITTI datasets.

Tae-Wook Um, Ki-Hyeon Kim, Hyun-Duck Choi et al.

MagicMirror uses 340K annotated images and GRPO-trained VLM for fine-grained artifact assessment, advancing model defect detection.

Jia Wang, Jie Hu, Xiaoqi Ma et al.

The OnlineHOI framework achieves state-of-the-art results in online human-object interaction generation and perception on Core4D and OAKINK2 datasets.

Yihong Ji, Yunze Liu, Yiyao Zhuo et al.

InterAct enhances 3D human-object interaction data quality with a unified optimization framework, expanding the dataset to 30.70 hours.

Sirui Xu, Dongting Li, Yucheng Zhang et al.

Dark-ISP enhances low-light object detection by directly processing Bayer RAW images, outperforming existing methods.

Jiasheng Guo, Xin Gao, Yuxiang Yan et al.

RewardDance scales reward models up to 26B parameters, improving visual generation quality and robustness against reward hacking.

Jie Wu, Yu Gao, Zilyu Ye et al.

VIRAL aligns visual representations to enhance multimodal large models' performance on visual tasks, with an average improvement of 9.4%.

Heeji Yoon, Jaewoo Jung, Junwan Kim et al.

UFC method achieves spatial control in diffusion models with few samples, nearing fully supervised baselines.

Kiet T. Nguyen, Chanhyuk Lee, Donggyun Kim et al.

FlowSeek integrates depth foundation models and motion bases for low-resource, high-accuracy optical flow estimation, outperforming SOTA by 10-15%.

Matteo Poggi, Fabio Tosi